Proliferation of (outdated) nvidia management packages

After I found out about scalene, and that conda-forge [isn't](https://github.com/conda-forge/staged-recipes/issues/17059) packaging it yet, I did my usual packager thing of checking the [requirements](https://github.com/plasma-umass/scalene/blob/v1.3.16/setup.py#L136-L142), and whether they're packaged for conda-forge already.

Looking for `nvidia-ml-py` in various variants lead me to a bunch of feedstocks that are all doing similar things, most of them outdated or obsolete:
- https://github.com/conda-forge/pynvml-feedstock/ -> https://github.com/gpuopenanalytics/pynvml (kinda up to date, but different version (`11.0.0` vs. `11..` of the official version - it's unclear if those are compatible); upstream notes:
> As of version 11.0.0, the NVML-wrappers used in pynvml are identical to those published through nvidia-ml-py.
- https://github.com/conda-forge/py3nvml-feedstock -> https://github.com/fbcotter/py3nvml (unofficial fork of `nvidia-ml-py` at a time when it didn't support python 3)
- https://github.com/conda-forge/nvidia-ml-feedstock -> https://github.com/nicolargo/nvidia-ml-py3 (dead feedstock for a dead python 3 port).

I think at least the last two should be archived, but that still leaves a gap of not being able to use `nvidia-ml-py` in the same version as the PyPI upstream. I guess one option would be to repackage the `pip` wheels?

Now that conda-forge can redistribute stuff from nvidia, I hope that this situation can be cleaned up or at least improved.

CC @jakirkham @leofang @kkraus14